In this work, we aim to extend the traditional ILP methods to hypergraphs whose events are labeled with time intervals. In the following section, we first formally define this representation, namely temporal hypergraph. Then, we discuss the random walk (RW) algorithm on a hypergraph, as RW is the fundamental mechanism of a family of widely used ILP methods, that is the backward-chaining methods. We revisit the notion of B-connectivity on hypergraphs and propose the multi-start random B-walk algorithm that explores the hypergraph given a set of starting points. To generalize the temporal relation, we incorporate Allen's interval algebra [1]} and characterize events with the interval operators such as Before and After. We learn temporal relations by resolving the time constraints with a constraint propagation algorithm modified from the path consistency algorithm.
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